ASTRAL: genome-scale coalescent-based species tree estimation
| Autor: | Tandy Warnow, M. S. Swenson, Siavash Mirarab, Rezwana Reaz, Md. Shamsuzzoha Bayzid, Théo Zimmermann |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
0106 biological sciences
Statistics and Probability Genetic Speciation Population Concatenation Biodiversity Genomics Biology computer.software_genre 010603 evolutionary biology 01 natural sciences Biochemistry Coalescent theory 03 medical and health sciences Phylogenetics Animals education Molecular Biology Phylogeny 030304 developmental biology Mammals 0303 health sciences education.field_of_study Tree (graph theory) Original Papers Computer Science Applications Computational Mathematics Computational Theory and Mathematics Genes Evolutionary biology Data Interpretation Statistical Evolution and Population Genomics Data mining Eccb 2014 Proceedings Papers Committee computer Algorithms |
| Zdroj: | Bioinformatics |
| ISSN: | 1367-4811 1367-4803 |
| Popis: | Motivation: Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions. Results: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy—improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods. ASTRAL is often more accurate than concatenation using maximum likelihood, except when ILS levels are low or there are too few gene trees. Availability and implementation: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral. Contact: warnow@illinois.edu Supplementary information: Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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